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•
0fe497d
1
Parent(s):
2694247
fix wordings and minor layout issue
Browse files- app_debug.py +2 -2
- app_leaderboard.py +8 -8
- app_text_classification.py +5 -5
- text_classification_ui_helpers.py +5 -2
- wordings.py +3 -3
app_debug.py
CHANGED
@@ -63,9 +63,9 @@ def get_queue_status():
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current = pipe.current
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if current is None:
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current = "None"
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-
return f'<div style="padding-top: 5%">Current job: {html.escape(current)} <br/>
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else:
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-
return '<div style="padding-top: 5%">No jobs
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def get_demo():
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current = pipe.current
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if current is None:
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current = "None"
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+
return f'<div style="padding-top: 5%">Current job: {html.escape(current)} <br/> Job queue: <br/> {"".join(get_jobs_info_in_queue())}</div>'
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else:
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+
return '<div style="padding-top: 5%">No jobs waiting, please submit an evaluation task from Text-Classification tab.</div>'
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def get_demo():
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app_leaderboard.py
CHANGED
@@ -96,25 +96,25 @@ def get_demo(leaderboard_tab):
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display_df = get_display_df(default_df) # the styled dataframe to display
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with gr.Row():
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-
with gr.Column():
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issue_columns_select = gr.CheckboxGroup(
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label="Issue Columns",
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choices=issue_columns,
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value=[],
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interactive=True,
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)
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with gr.Column():
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info_columns_select = gr.CheckboxGroup(
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label="Info Columns",
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choices=info_columns,
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value=default_columns,
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interactive=True,
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)
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with gr.Row():
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task_select = gr.Dropdown(
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label="Task",
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-
choices=["text_classification"
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value="text_classification",
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interactive=True,
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)
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display_df = get_display_df(default_df) # the styled dataframe to display
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with gr.Row():
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with gr.Column():
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info_columns_select = gr.CheckboxGroup(
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label="Info Columns",
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choices=info_columns,
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value=default_columns,
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interactive=True,
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+
)
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with gr.Column():
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issue_columns_select = gr.CheckboxGroup(
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label="Issue Columns",
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choices=issue_columns,
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value=[],
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interactive=True,
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)
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with gr.Row():
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task_select = gr.Dropdown(
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label="Task",
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choices=["text_classification"],
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value="text_classification",
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interactive=True,
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)
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app_text_classification.py
CHANGED
@@ -92,7 +92,7 @@ def get_demo():
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for _ in range(MAX_LABELS, MAX_LABELS + MAX_FEATURES):
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column_mappings.append(gr.Dropdown(visible=False))
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-
with gr.Accordion(label="Model Wrap
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gr.HTML(USE_INFERENCE_API_TIP)
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run_inference = gr.Checkbox(value=True, label="Run with Inference API")
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@@ -111,7 +111,7 @@ def get_demo():
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outputs=[inference_token_info],
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)
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-
with gr.Accordion(label="Scanner
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scanners = gr.CheckboxGroup(visible=True)
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@gr.on(triggers=[uid_label.change], inputs=[uid_label], outputs=[scanners])
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@@ -145,8 +145,8 @@ def get_demo():
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with gr.Row():
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logs = gr.Textbox(
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value=CHECK_LOG_SECTION_RAW,
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label="
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visible=
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every=0.5,
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)
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@@ -156,7 +156,7 @@ def get_demo():
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gr.on(
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triggers=[model_id_input.change],
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fn=get_related_datasets_from_leaderboard,
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inputs=[model_id_input],
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outputs=[dataset_id_input],
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).then(
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fn=check_dataset,
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for _ in range(MAX_LABELS, MAX_LABELS + MAX_FEATURES):
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column_mappings.append(gr.Dropdown(visible=False))
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+
with gr.Accordion(label="Model Wrap Advanced Config", open=True):
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gr.HTML(USE_INFERENCE_API_TIP)
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run_inference = gr.Checkbox(value=True, label="Run with Inference API")
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outputs=[inference_token_info],
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)
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+
with gr.Accordion(label="Scanner Advanced Config (optional)", open=False):
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scanners = gr.CheckboxGroup(visible=True)
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@gr.on(triggers=[uid_label.change], inputs=[uid_label], outputs=[scanners])
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with gr.Row():
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logs = gr.Textbox(
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value=CHECK_LOG_SECTION_RAW,
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label="Log",
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visible=True,
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every=0.5,
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)
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gr.on(
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triggers=[model_id_input.change],
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fn=get_related_datasets_from_leaderboard,
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inputs=[model_id_input, dataset_id_input],
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outputs=[dataset_id_input],
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).then(
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fn=check_dataset,
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text_classification_ui_helpers.py
CHANGED
@@ -43,7 +43,7 @@ MAX_FEATURES = 20
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ds_dict = None
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ds_config = None
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-
def get_related_datasets_from_leaderboard(model_id):
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records = leaderboard.records
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model_id = strip_model_id_from_url(model_id)
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model_records = records[records["model_id"] == model_id]
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@@ -52,7 +52,10 @@ def get_related_datasets_from_leaderboard(model_id):
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if len(datasets_unique) == 0:
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return gr.update(choices=[])
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-
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logger = logging.getLogger(__file__)
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ds_dict = None
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ds_config = None
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+
def get_related_datasets_from_leaderboard(model_id, dataset_id_input):
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records = leaderboard.records
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model_id = strip_model_id_from_url(model_id)
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model_records = records[records["model_id"] == model_id]
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if len(datasets_unique) == 0:
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return gr.update(choices=[])
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if dataset_id_input in datasets_unique:
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return gr.update(choices=datasets_unique)
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return gr.update(choices=datasets_unique, value="")
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logger = logging.getLogger(__file__)
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wordings.py
CHANGED
@@ -1,7 +1,9 @@
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INTRODUCTION_MD = """
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<h1 style="text-align: center;">
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🐢Giskard Evaluator - Text Classification
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</h1>
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Welcome to the Giskard Evaluator Space! Get a model vulnerability report immediately by simply sharing your model and dataset id below.
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You can also checkout our library documentation <a href="https://docs.giskard.ai/en/latest/getting_started/quickstart/index.html">here</a>.
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"""
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@@ -26,9 +28,7 @@ CHECK_CONFIG_OR_SPLIT_RAW = """
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Please check your dataset config or split.
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"""
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CHECK_LOG_SECTION_RAW = """
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Your have successfully submitted a Giskard evaluation. Further details are available in the Logs tab. You can find your report will be posted to your model's community discussion.
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"""
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PREDICTION_SAMPLE_MD = """
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<h1 style="text-align: center;">
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INTRODUCTION_MD = """
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<div style="display: flex; justify-content: center;">
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<h1 style="text-align: center;">
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🐢Giskard Evaluator - Text Classification
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</h1>
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</div>
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Welcome to the Giskard Evaluator Space! Get a model vulnerability report immediately by simply sharing your model and dataset id below.
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You can also checkout our library documentation <a href="https://docs.giskard.ai/en/latest/getting_started/quickstart/index.html">here</a>.
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"""
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Please check your dataset config or split.
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"""
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+
CHECK_LOG_SECTION_RAW = """Your have successfully submitted a Giskard evaluation job. Further details are available in the Logs tab. You can find your report posted in your model's community discussion section."""
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PREDICTION_SAMPLE_MD = """
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<h1 style="text-align: center;">
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